Search

An experimental study of the response of an intact native ecosystem to increased CO2 reveals that native ecosystems do not always show positive responses to increased CO2 and that these responses might often be complicated. A CO2 level doubling reinstates total homeostasis of the CO2 flux while CO2 doubling and exposure of ecosystems to high temperatures result in a continuous fertilization impact on total carbon sequestration. The difference is due to increased sink activity due to high temperature effects on growth and to increased nutrient supply due to elevated mineralization.

Data from Alaska's North Slope show the tundra has become a net source of carbon dioxide (CO2). The tundra has historically been a CO2 sink as the carbon cycle stored carbon in the form of only partially decomposed plant remains. Recent warming may have lowered the water table which, in turn, increased plant decomposition and concentration of atmospheric CO2. If the recent warming resulted from increased greenhouse gas concentration, then the tundra ecosystem may be part of a positive feedback loop with global warming and atmospheric CO2.

The rates, processes, and controls on Arctic cold period soil carbon loss are still poorly understood. To understand one component of winter CO2 loss in the atmosphere, continuous measurements of soil (CO2) were made and compared to ecosystem scale CO2 fluxes. Measurements of soil (CO2) were made near Utqiaġvik, Alaska from the beginning of soil thaw in summer 2005 to spring 2007. In the summer, soil (CO2) rose with increased soil temperature, reaching value orders of magnitude higher than the atmospheric (CO2). Soil (CO2) initially decreased at the end of summer and beginning of fall but then increased subsequent to soil freezing. Due to complex changes in biological activity, storage, and transport processes, soil (CO2) was then approximately doubled than that was observed in the summer. After reaching peak concentrations in November, soil (CO2) steeply decreased over a couple of weeks, suggesting a substantial release of CO2 into the atmosphere and movement within the soil column. Eddy covariance (EC) measurements showed variable but continued emissions of CO2 to the atmosphere during freezeup. The disconnect between soil (CO2) and landscape level fluxes may be attributed to the spatiotemporal heterogeneity in release of high concentrations of soil (CO2) to the atmosphere during the fall; and when integrated over the area of the EC tower footprint, do not frequently result in detectable emission events. Continued monitoring of fall and winter soil (CO2) and ecosystem fluxes will be vital for further understanding the variability of interannual Arctic CO2 emissions. Key Points: Soil (CO2) doubled in the fall, likely attributable to complex changes in biological activity, storage, and transport processes amidst soil freezingSoil (CO2) was significantly controlled by soil temperature and maintained substantial values well below zero (at −20 cm soil (CO2) concentrations were in the order of 6.40 ± 0.19% through freezing)Peak increases in soil (CO2) were not captured by ecosystem scale CO2 fluxes, suggesting a disconnect between complex and spatially heterogenous driving processes [ABSTRACT FROM AUTHOR]

Salt marshes and seagrass meadows can sequester and store high quantities of organic carbon (OC) in their sediments relative to other marine and terrestrial habitats. Assessing carbon stocks, carbon sources, and the transfer of carbon between habitats within coastal seascapes are each integral in identifying the role of blue carbon habitats in coastal carbon cycling. Here, we quantified carbon stocks, sources, and exchanges in seagrass meadows, salt marshes, and unvegetated sediments in six bays along the Pacific coast of California. The salt marshes studied here contained approximately twice as much OC as did seagrass meadows, 23.51 ± 1.77 kg OC m-3 compared to 11.01 ± 1.18 kg OC m-3, respectively. Both seagrass and salt marsh sediment carbon stocks were higher than previous estimates from this region but lower than global and U.S.-wide averages, respectively. Seagrass-derived carbon was deposited annually into adjacent marshes during fall seagrass senescence. However, isotope mixing models estimate that negligible amounts of this seagrass material were ultimately buried in underlying sediment. Rather, the vast majority of OC in sediment across sites was likely derived from planktonic/benthic diatoms and C3 salt marsh plants. [ABSTRACT FROM AUTHOR]

Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM‐Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low‐centered polygon (LCP) center, LCP transition, LCP rim, high‐centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM‐Microbe model against static‐chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low‐elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high‐elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2 + H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area‐weighted approach before validation against EC‐measured CH4 fluxes. The model underestimated the EC‐measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model‐data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape. Key Points: The CLM‐microbe model is able to simulate microtopographical impacts on CO2 and CH4 flux in the ArcticSubstrates availability for methanogenesis is the most important factor determining CH4 emissionThe strong microtopographic impacts call for a model‐data integration framework to better understand and predict C flux in the Arctic [ABSTRACT FROM AUTHOR]

Abstract. Regional estimates of arctic ecosystem [CO.sub.2] exchange are required because of the large soil carbon stocks located in arctic regions, the potentially large global-scale feedbacks associated with climate-change-induced alterations [...]

Abstract: A central challenge to understanding how climate anomalies, such as drought and heatwaves, impact the terrestrial carbon cycle, is quantification and scaling of spatial and temporal variation in ecosystem gross primary productivity (GPP). Existing empirical and model‐based satellite broadband spectra‐based products have been shown to miss critical variation in GPP. Here, we evaluate the potential of high spectral resolution (10 nm) shortwave (400–2,500 nm) imagery to better detect spatial and temporal variations in GPP across a range of ecosystems, including forests, grassland‐savannas, wetlands, and shrublands in a water‐stressed region. Estimates of GPP from eddy covariance observations were compared against airborne hyperspectral imagery, collected across California during the 2013–2014 HyspIRI airborne preparatory campaign. Observations from 19 flux towers across 23 flight campaigns (102 total image‐flux tower pairs) showed GPP to be strongly correlated to a suite of spectral wavelengths and band ratios associated with foliar physiology and chemistry. A partial least squares regression (PLSR) modeling approach was then used to predict GPP with higher validation accuracy (adjusted R2 = 0.71) and low bias (0.04) compared to existing broadband approaches (e.g., adjusted R2 = 0.68 and bias = −5.71 with the Sims et al. model). Significant wavelengths contributing to the PLSR include those previously shown to coincide with Rubisco (wavelengths 1,680, 1,740, and 2,290 nm) and Vcmax (wavelengths 1,680, 1,722, 1,732, 1,760, and 2,300 nm). These results provide strong evidence that advances in satellite spectral resolution offer significant promise for improved satellite‐based monitoring of GPP variability across a diverse range of terrestrial ecosystems. [ABSTRACT FROM AUTHOR]

Arctic tundra ecosystems are a major source of methane (CH4), the variability of which is affected by local environmental and climatic factors, such as water table depth, microtopography, and the spatial heterogeneity of the vegetation communities present. There is a disconnect between the measurement scales for CH4 fluxes, which can be measured with chambers at one-meter resolution and eddy covariance towers at 100-1000 m, whereas model estimates are typically made at the ∼100 km scale. Therefore, it is critical to upscale site level measurements to the larger scale for model comparison. As vegetation has a critical role in explaining the variability of CH4 fluxes across the tundra landscape, we tested whether remotely-sensed maps of vegetation could be used to upscale fluxes to larger scales. The objectives of this study are to compare four different methods for mapping and two methods for upscaling plot-level CH4 emissions to the measurements from EC towers. We show that linear discriminant analysis (LDA) provides the most accurate representation of the tundra vegetation within the EC tower footprints (classification accuracies of between 65% and 88%). The upscaled CH4 emissions using the areal fraction of the vegetation communities showed a positive correlation (between 0.57 and 0.81) with EC tower measurements, irrespective of the mapping method. The area-weighted footprint model outperformed the simple area-weighted method, achieving a correlation of 0.88 when using the vegetation map produced with the LDA classifier. These results suggest that the high spatial heterogeneity of the tundra vegetation has a strong impact on the flux, and variation indicates the potential impact of environmental or climatic parameters on the fluxes. Nonetheless, assimilating remotely-sensed vegetation maps of tundra in a footprint model was successful in upscaling fluxes across scales. [ABSTRACT FROM AUTHOR]